High-resolution optical coherence tomography using a multi-level diffractive lens.

This study aimed to evaluate a novel real-time rotational optical coherence tomography (OCT) imaging system (OCTIS) with a fiber-optic probe to look at endometrium and to correlate the OCTIS images with standard histology. OCT could obtain real-time images resembling histological examination. With recent development of customized probes, it allows OCT to be used in the field of gynecology.This is a pilot, prospective, ex-vivo and observational study. Women underwent hysterectomy for various gynecological conditions were recruited and OCTIS images were obtained from endometrium of 15 fresh uterus specimens immediately after hysterectomy. The excised uterus was cut open and OCTIS imaging was obtained. The scanned region of endometrium was excised for histological examination and OCTIS images were precisely compared to corresponding histological images and ultrasound images. Blinded qualitative analysis on OCTIS images was performed by 2 assessors to determine inter-rating reliability on the histopathological diagnosis.Epithelium, glands, cysts, and stroma of endometrium were clearly seen by the OCTIS. Different phases of menstrual cycle of normal endometrium could be differentiated and pathological condition such as hyperplastic and dysplasic endometrium, which corresponded well with histological findings, could be identified. The inter-rater reliability between assessors on overall OCTIS endometrium and neoplastic OCTIS endometrium was moderate (Kendall τb of 0.58) and substantial (Kendall τb of 0.76), respectively.OCTIS can provide real-time, high-resolution and rotational imaging modality to view endometrial structure with high consistency with histological examination and satisfactory agreement between observers. It has a great potential to be developed in the clinical use of endometrial assessment for gynecological applications.

To construct swept source optical coherence tomography (SS-OCT) imaging system for root canal endoscopy, and to evaluate the accuracy of diagnosing artificial root fractures. An ultra-high-speed (40 kHz) swept laser source was developed based on the piezoelectric tuning filter and the Fourier domain mode locking (FDML) swept laser technology (patent number: 200620135940.2). Ultra-miniature gradient index lens technology (patent number: 201320241218.7) was used to create a thin endoscopic probe with a diameter of 0.86 mm for real-time image transmission. The SS-OCT light source had a wavelength of 1 310 nm and a bandwidth of 100 nm. The axial and transverse image resolutions were 15 μm and 25 μm, respectively. Artificial fractures were created on human mandibular premolars with single root and the premolar roots were prepared to 41 horizontal sections (1 mm thick). 27 root sections with fractures (width: 52-284 μm) and 14 the sections without fractures were observed under an optical stereomicroscope with a cold light source as the gold standard. The horizontal root sections were scanned by self-developed SS-OCT imaging system for root canal endoscopy with a central wavelength of 1 310 nm and bandwidth of 100 nm. The data were reconstructed with 30 μm thick slices at an interval of 30 μm. Two observers, a radiologist and an endodontist, were trained and independently evaluated all the reconstructed images blindly. The diagnostic performance of SS-OCT imaging system was calculated, and statistical analysis was performed. SS-OCT root canal endoscopic imaging system composed of high-speed swept laser source, fiber coupler, endoscopic probe, reference arm and differential detector. Root sections could be scanned by SS-OCT and imaged in realtime at a depth of 1 to 2 mm. The kappa value for interobserver agreement was 0.792, and the intraobserver agreement was 1.000 and 0.709 for two observers respectively. All of 27 fractured root sections and 12 of 14 root sections without fractures were accurately diagnosed while 2 unfractured root sections were misdiagnosed. The sensitivity was 1.000 and the specificity was 0.857 for diagnosis of artificial root fractures by SS-OCT. The positive predictive value (PPV), negative predictive value (NPV) and the overall accuracy rate were 0.931, 1.000 and 0.951 respectively. The swept source optical coherence tomography imaging system for root canal endoscopy is a promising imaging method for observing root fractures．.

A frequency swept source optical coherence tomography (OCT) imaging system is proposed. The frequency swept source used in the system is a Fourier-domain mode-locked (FDML) laser which has a narrow instantaneous linewidth due to the nonlinear spectrum narrowing effect generated by the nonlinear semiconductor optical amplifier (SOA) used in the FDML laser ring cavity. Therefore, the OCT imaging system has the ability to achieve a large imaging depth. The concept is verified in the experiment, which demonstrates a clear two-dimensional target image and a large imaging depth up to 14 mm.

Regenerative therapies such as stem cell therapies are an area of active investigation that will likely play an important role in the future to improve vision loss from retinal diseases including macular degeneration and retinitis pigmentosa. It is important to visualize these cells after administration to determine their fate and effect. In this study, an advanced non-invasive photoacoustic microscopy (PAM) and optical coherence tomography (OCT) imaging system was developed to monitor cells in vivo. To boost the sensitivity of PAM and OCT, novel ultrapure functionalized chain-like gold nanoparticle (CGNP) clusters were synthesized and cultured into a precursor human retinal pigment epithelial cell line with differentiated properties (ARPE-19) cells. The fabricated CGNP clusters have redshifted plasmonic peak absorption from 520nm to 650nm, resulting in reduced background signal from hemoglobin. The position of cells following subretinal injection into the rabbit retina having laser injury is selectively tracked longitudinally in vivo using integrated photoacoustic microscopy (PAM) and OCT over 3 months in 3 rabbits. PAM images obtained at two different optical wavelengths of 578 nm and 650 nm were overlaid on the same image plane and on the OCT image allowed to distinguish transplanted cells from the adjacent native choroidal vessels and track the migration of the cells over time. Quantification of PAM and OCT signals illustrated that the PAM signal increased by 30-fold, and OCT signal increased by 180 %. Histological analysis confirmed that ARPE-19 cells migrated to the injured sites and correlated with the location noted on the PAM/OCT imaging. This work provides a comprehensive imaging and nanoparticle system that could be used for labeling and tracking of cell-based regenerative therapies.

In this paper, five types of tissues, human enamel, human cortical bone, human trabecular bone, muscular tissue, and fatty tissue were imaged <i>ex vivo</i> using optical coherence tomography (OCT). The specimens were prepared in blocks of 5 x 5 x 3 mm (width x length x height). The OCT imaging system was a swept source OCT system operating at wavelengths ranging between 1250 nm and 1360 nm with an average power of 18 mW and a scan rate of 50 to 100 kHz. The imaging probe was placed on top of a 2 x 2 cm stabilizing device to maintain a standard distance from the samples. Ten image samples from each type of tissue were obtained. To acquire images with minimum inhomogeneity, imaging was performed multiple times at different points. Based on the observed texture differences between OCT images of soft and hard tissues, spatial and spectral features were quantitatively extracted from the OCT images. The Radon transform from angles of 0 deg to 90 deg was computed, averaged over all the angles, normalized to peak at unity, and then fitted with Gaussian function. The mean absolute values of the spatial frequency components of the OCT image were considered as a feature, where 2-D fast Fourier transform (FFT) was done to OCT images. These OCT features can reliably differentiate between a range of hard and soft tissues, and could be extremely valuable in assisting dentists for <i>in vivo</i> evaluation of oral tissues and early detection of pathologic changes in tissues.

For the study of disease mechanisms and the development of novel therapeutic strategies for retinal pathologies in human, rodent models play an important role. Nowadays, optical coherence tomography (OCT) allows three-dimensional investigation of retinal events over time. However, a detailed analysis of how different retinal degenerations are reflected in OCT images is still lacking in the biomedical field. Therefore, we use OCT to visualize retinal degeneration in specific mouse models in order to study disease progression <i>in vivo</i> and improve image interpretation of this noninvasive modality. We use a self-developed spectral domain OCT system for simultaneous dual-band imaging in the 0.8 &mu;m- and 1.3 &mu;m-wavelength range – the two most common spectral bands in biomedical OCT. A fiber-coupled ophthalmic scanning unit allows flexible imaging of the eye with a high axial resolution of 3 - 4 &mu;m in tissue. Four different mouse models consisting of one genetic (rhodopsin-deficient and three induced retinal degenerations (sodium iodate-induced damage, light-induced photoreceptor damage and Kainate neurotoxin damage) were investigated. OCT imaging was performed daily or weekly, depending on the specific degeneration model, over a time period of up to 9 weeks. Individual retinal layers that were affected by the specific degeneration could successfully be identified and monitored over the observation time period. Therefore, longitudinal OCT studies deliver reliable information about the retinal microstructure and the time course of retinal degeneration processes <i>in vivo</i>.

Noninvasive and high-speed optical coherence tomography (OCT) systems have been widely deployed for daily clinical uses. High-resolution OCTs are advancing rapidly; however, grey-level OCT images are not easy to read for pathologists due to the lack of diagnosis specificity compared with hematoxylin and eosin (H&amp;E) stained images. This work presents an OCT to H&amp;E image translation model to convert the OCT images to H&amp;E-like stained images using unpaired OCT and H&amp;E datasets. “H&amp;E like” means the stratum corneum (SC) boundary and the dermal-epidermal junction (DEJ) of the OCT and the translated images are consistent. Pre-trained segmentation models for the DEJ and the SC are exploited to enhance the performance of anatomical image translation and reduce the DEJ and SC lower boundary errors to ±2.3 and ±1.7 μm, respectively. A pre-trained VGG16 network extracts the features of the nuclei. Pearson's correlation coefficient of the nuclei location and size consistency is 84% ± 1%. As a result, in vivo medical image translation accuracy with cellular resolution was achieved.

Clinical Characterization of Coronary Atherosclerosis With Dual-Modality OCT and Near-Infrared Autofluorescence Imaging

We present a deep learning-based digital refocusing approach to extend depth of focus for optical coherence tomography (OCT) in this paper. We built pixel-level registered pairs of en face low-resolution (LR) and high-resolution (HR) OCT images based on experimental data and introduced the receptive field block into the generative adversarial networks to learn the complex mapping relationship between LR-HR image pairs. It was demonstrated by results of phantom and biological samples that the lateral resolutions of OCT images were improved in a large imaging depth clearly. We firmly believe deep learning methods have broad prospects in optimizing OCT imaging.

Summary form only given. Optical coherence tomography (OCT) imaging can resolve many of the changes associated with neoplasia and may provide a tool for in vivo real-time evaluation of tissue and biopsy guidance to help improve the diagnosis of early neoplasias, resulting in more successful treatment. OCT is a new imaging technology that allows cross-sectional imaging of nontransparent tissue. A low-coherence Michelson interferometer is used to measure echo time delays of reflected light from scattering tissue. The light beam is scanned across the tissue to produce two- and three-dimensional data sets. This technique has been extensively applied to imaging in ophthalmology and more recently to nontransparent tissues. High-resolution and high-speed OCT imaging has been achieved using broad bandwidth mode-locked lasers as short-coherence light sources. Recently, in vivo catheter/endoscope based imaging of the gastrointestinal and pulmonary tracts has been demonstrated in a rabbit model. In order to evaluate the ability of OCT to image cellular morphology in vivo, an animal model was used. OCT imaging in vitro was also performed on a series of human tissues of varying degrees of neoplastic infiltration, including colon, cervix, uterus, and lung.

Accurate segmentation of tumor-infected regions in retinal Optical Coherence Tomography (OCT) images is critical for early diagnosis and clinical decision-making. However, conventional deep learning and transformer-based models often struggle to delineate overlapping and inter-dependent pixel features, leading to reduced segmentation precision. This study proposes a novel Dependent Inter-Feature Segmentation Method (DIFSM) to improve the localization and segmentation of retinal tumor regions in OCT images. The proposed DIFSM framework integrates advanced image preprocessing, inter-feature dependency analysis, and a Vision Transformer (ViT) architecture to distinguish differentiable and non-differentiable features. Overlapping pixel regions are identified through inter-feature intensity and gradient analysis, which are indicative of tumor-affected areas. The Vision Transformer is trained using matched and unmatched inter-feature representations to enhance contextual learning and resolve feature ambiguities. Experiments were conducted on the OCTID dataset comprising high-resolution retinal OCT images, and performance was evaluated using Dice coefficient, Intersection over Union (IoU), precision, sensitivity, specificity, and Mean Square Matching Error (MSME). Comparative analysis was performed against state-of-the-art segmentation models. The proposed DIFSM model achieved a Dice coefficient of 96.2% and an IoU of 94.8%, demonstrating excellent spatial overlap with expert-validated tumor regions. Precision, sensitivity, and specificity reached 96.8%, 96.6%, and 96.7%, respectively, while MSME was reduced to 6.11%. Compared to existing methods, DIFSM improved segmentation accuracy by 14.39%, precision by 14.11%, and reduced MSME by 13.5%. The model consistently outperformed benchmark approaches in detecting macular hole and central serous retinopathy-associated tumor regions while maintaining robustness to noise and structural variability. The proposed DIFSM framework effectively addresses the limitations of existing OCT segmentation methods by explicitly modeling inter-feature dependencies and resolving overlapping pixel ambiguities using a Vision Transformer. The significant improvements in segmentation accuracy and error reduction highlight its potential as a reliable and clinically applicable tool for automated retinal tumor detection in ophthalmic imaging. DIFSM offers a promising direction for enhancing OCT-based diagnostic systems and supporting ophthalmologists in early disease identification and treatment planning.

An Optical Coherence Tomography (OCT) imaging system has been designed and constructed to acquire images of scattering biological samples. By simultaneously acquiring and displaying high resolution en-face (C-scan) OCT and Laser Scanning Confocal images of Drosophila melanogaster embryos we demonstrate the potential of the system to be used as a powerful tool for imaging in Drosophila embryonic development. The system can equally be used for non invasive visualizations and measurements of the movement of Drosophila melanogaster larval heart and can easily be switched in the OCT B-scan regime. The confocal channel adds guidance as the specimen can be quickly located and this makes the use of the system in a large scale gene screen feasible.

We develop a novel enhanced laser-based elastography technique that utilizes an optical coherence tomography (OCT) imaging system. This enhancement combines the capabilities of OCT with an advanced phase extraction technique, aiming to increase the precision of biomechanical measurements in soft tissues. Our approach utilizes the discrete cosine transform (DCT) for phase extraction, overcoming the limitations of vector-based methods in handling complex geometries and large displacements. Unlike fast Fourier transform-based unwrapping, DCT ensures thar the result is artifact-free. This advancement refines spatial detail in optical coherence elastography (OCE), enabling accurate mapping of tissue elasticity and structural variations. By eliminating windowing constraints, our method offers a faster, more robust solution for biomechanical diagnostics. In this study, we introduce a micro-elastography system that utilizes a 4 ohm speaker as a mechanical excitation source to apply controlled, quasi-static compressions. This system, combined with a high-speed, 100 kHz swept-source OCT laser, enables rapid data acquisition and straightforward phase-to-strain conversion. Our findings demonstrate the system’s capability of providing accurate strain mapping across a range of samples, delivering reliable elastic information despite the challenges posed by non-linear and non-uniform tissue boundaries. This study showcases the potential of DCT-based OCE to enhance clinical diagnostics and improve the characterization of diseased and tumor boundaries in soft tissues.

We recently developed an approach to characterize local nonlinear, anisotropic mechanical properties of murine arteries by combining biaxial extension-distension testing, panoramic digital image correlation, and an inverse method based on the principle of virtual power. This experimental-computational approach was illustrated for the normal murine abdominal aorta assuming uniform wall thickness. Here, however, we extend our prior approach by adding an optical coherence tomography (OCT) imaging system that permits local reconstructions of wall thickness. This multimodality approach is then used to characterize spatial variations of material and structural properties in ascending thoracic aortic aneurysms (aTAA) from two genetically modified mouse models (fibrillin-1 and fibulin-4 deficient) and to compare them with those from angiotensin II-infused apolipoprotein E-deficient and wild-type control ascending aortas. Local values of stored elastic energy and biaxial material stiffness, computed from spatial distributions of the best fit material parameters, varied significantly with circumferential position (inner vs. outer curvature, ventral vs. dorsal sides) across genotypes and treatments. Importantly, these data reveal an inverse relationship between material stiffness and wall thickness that underlies a general linear relationship between stiffness and wall stress across aTAAs. OCT images also revealed sites of advanced medial degeneration, which were captured by the inverse material characterization. Quantification of histological data further provided high-resolution local correlations among multiple mechanical metrics and wall microstructure. This is the first time that such structural defects and local properties have been characterized mechanically, which can better inform computational models of aortopathy that seek to predict where dissection or rupture may initiate.

&lt;p&gt;In this work, we explored the potential of measuring shear wave propagation using optical coherence elastography (OCE) in an inhomogeneous phantom and carotid artery samples based on a sweptsource optical coherence tomography (OCT) system. Shear waves were generated using a piezoelectric transducer transmitting sine-wave bursts of 400 μs duration, applying acoustic radiation force (ARF) to inhomogeneous phantoms and carotid artery samples, synchronized with a swept-source OCT (SS-OCT) imaging system. The phantoms were composed of gelatin and titanium dioxide whereas the carotid artery samples were embedded in gel. Differential OCT phase maps, measured with and without the ARF, detected the microscopic displacement generated by shear wave propagation in these phantoms and samples of different stiffness. We present the technique for calculating tissue mechanical properties by propagating shear waves in inhomogeneous tissue equivalent phantoms and carotid artery samples using the ARF of an ultrasound transducer, and measuring the shear wave speed and its associated properties in the different layers with OCT phase maps. This method lays the foundation for future in-vitro and in-vivo studies of mechanical property measurements of biological tissues such as vascular tissues, where normal and pathological structures may exhibit significant contrast in the shear modulus. &lt;/p&gt;